The Industrial Internet of Things (IIoT) is a technology that is used in manufacturing, warehouses, factories, and laboratories. It is used to automate and simplify manufacturing processes.
Some examples of IIoT:
With the help of IIoT technology, it is possible to reduce production costs and avoid losses. Sensors on the equipment will inform about the need for maintenance. A climate control system will monitor that equipment does not overheat. Beacons on transports will indicate when a shipment is being delivered. The data that these sensors and beacons collect can be downloaded into analysis systems to make predictions and study the entire plant.
The IIoT system consists of several interconnected components that enable efficient digital process change in the enterprise:
It is no secret that all businesses sooner or later face the problem of outdated industrial equipment, meters, and sensors, which, although they perform the assigned tasks, do not have digital communication interfaces and automatic remote monitoring. Such limitations do not allow them to "fit" into the ecosystem of the Industrial Internet of Things that is being implemented, which means that the digitalization of this technological process cannot be achieved. If we talk about just one industrial facility and a small number of analog meters, the problem does not seem global. But if it is a large holding or concern, where there are many industrial sites and facilities, in this case, the transition can be very complicated, and choosing the right solution at the design stage will play a key role in the future.
Such a problem of taking states and readings from analog meters and sensors can be solved, and there are two main ways to do it.
The first way is to upgrade the existing monitoring scheme without replacing the existing meters and sensors.
The second way is to replace analog meters and sensors with their digital counterparts with wired or wireless interfaces for remote reading or status.
We have chosen to go the second way. The complete replacement of analog meters with digital ones increases the time and financial costs at the start, but in fact, is a profitable option in the long-term development and implementation of digitalization policy in the enterprise. For the development of any enterprise, it is important to think about replacing equipment that will not only automate the operation of the company but also receive more accurate indicators and signals.
Electricity affects our lives in many ways, from everyday life to business and industry. That's why it's considered an important factor in the economy. In the 21st century, the growth of digital innovation depends on efficient and reliable energy infrastructure. Therefore, it is necessary to improve energy production and delivery by making them smarter, more efficient, more reliable, and more transparent.
Smart meters not only record electricity consumption but also monitor and report abnormalities such as voltage dips and spikes. This allows you to use smart meters to monitor your electrical circuit, read data from them remotely, and manage your energy consumption more efficiently.
Our task was to organize the remote collection of readings from electric meters.
We took a modern electronic meter with an RS485 interface. We use meters manufactured by Incotex Mercury, modifications 203.2T or 204.
From the official documentation from the site Incotex - different protocols are used to poll meters:
To solve the problem I have developed a script that is connected to the meter via a converter RS485 over TCP/IP and takes the required readings for both protocols.
SNR-ERD-4s is a multifunctional device for remote control and monitoring with Ethernet <-> RS485 interface converter function.
For the development I used Python3. The input to the script is the IP address of the converter, the used TCP port, and the serial number of the meter. when using the protocol for three-phase meters, the login and password can also be transmitted. The script measures the Active and Reactive energy and gives information for each of the phases. Since the meters are multi-tariff, the consumption for each of the tariffs is output. The script returns the data in JSON format, which facilitates integration into various data processing and monitoring systems.
./mercury-em.py --proto=m206 --serial 39075510 --host 172.26.1.250 --port 50 | jq .
{
"info": {
"V": 208.7,
"A": 7.78,
"P": 1580,
"freq": 49.88
},
"energy": {
"A+_T1": 28382.38,
"A+_T2": 15782.03,
"A+_T3": 0,
"A+_T4": 0,
"A+sum": 44164.41
}
}
The final version of the script I posted on github.com
Links: